The chronology of a large ice-dammed lake and the Barents–Kara Ice Sheet advances, Northern Russia

Beach and shoreface sediments deposited in the more than 800-km long ice-dammed Lake Komi in northern European Russia have been investigated and dated. The lake flooded the lowland areas between the Barents–Kara Ice Sheet in the north and the continental drainage divide in the south. Shoreline facies have been dated by 18 optical stimulated luminescence (OSL) dates, most of which are closely grouped in the range 80–100 ka, with a mean of 88±3 ka. This implies that that the Barents–Kara Ice Sheet had its Late Pleistocene maximum extension during the Early Weichselian, probably in the cold interval (Rederstall) between the Brørup and Odderade interstadials of western Europe, correlated with marine isotope stage 5b. This is in strong contrast to the Scandinavian and North American ice sheets, which had their maxima in isotope stage 2, about 20 ka. Field and air photo interpretations suggest that Lake Komi was dammed by the ice advance, which formed the Harbei–Harmon–Sopkay Moraines. These has earlier been correlated with the Markhida moraine across the Pechora River Valley and its western extension. However, OSL dates on fluvial sediments below the Markhida moraine have yielded ages as young as 60 ka. This suggests that the Russian mainland was inundated by two major ice sheet advances from the Barents–Kara seas after the last interglacial: one during the Early Weichselian (about 90 ka) that dammed Lake Komi and one during the Middle Weichselian (about 60 ka). Normal fluvial drainage prevailed during the Late Weichselian, when the ice front was located offshore.     

The influence of a non‐associated flow rule on the calculation of the factor of safety of soil slopes

This paper presents a method that incorporates a non‐associated flow rule into the limit analysis to investigate the influence of the dilatancy angle on the factor of safety for the slope stability analysis. The proposed method retain's the advantage of the upper bound method, which is simple and has no stress involvement in the calculation of the energy dissipation and the factor of safety. Copyright © 2001 John Wiley & Sons, Ltd.     

Wolf-Rayet stars

Summary Recent literature on Population I Wolf-Rayet star research extending from the Milky Way to blue compact dwarf galaxies is reviewed, broken down into inventory, basic parameters and galactic distribution, atmospheres, binaries, intrinsic variability, mass loss, enrichment and evolution. Also the incidence of Wolf-Rayet stars with variable non-thermal radio emission, excess X-ray fluxes, and episodic/periodic IR excesses is reviewed. These phenomena appear to be associated with wind-wind interaction in wide long-period WR+OB binaries and with wind-compact object interaction in WR+c binaries, with orbit sizes of the order of magnitude of the WR radio photosphere sizes or larger.     

1999年8月11日日全食期间的重力吸引效应研究

对1999年8月11日日全食阴影扫过欧洲期间,设在Annelles,Uccle,Walferdange和Bondy弹簧和超导重力仪的记录进行了分析.为了确定月亮对太阳万有引力可能的遮挡效应的极限,对超导和弹簧重力仪记录进行了比较.同时也对LCR和阿斯卡尼亚重力仪观测结果进行了讨论.结论是如果日食重力吸引效应存在,它应在超导重力仪±1 nm/s2(0.1×10-8ms-2)的观测精度范围之内.研究发现在以上情形下,弹簧和超导重力仪都在它们的精度范围内工作,并且日食引起的异常环境干扰可能使重力信号有重大的改变.     

Cokriging nonstationary data

Universal cokriging is used to obtain predictions when dealing with multivariate random functions. An important type of nonstationarity is defined in terms of multivariate random functions with increments which are stationary of orderk. The covariance between increments of different variables is modeled by means of the pseudo-cross-covariance function. Criteria are formulated to which the parameters of pseudo-cross-covariance functions must comply so as to ensure positive-definiteness. Cokriging equations and the induced cokriging equations are given. The study is illustrated by an example from soil science.     

On least squares estimation of generalized covariance functions

Least squares estimation (LSE) is theoretically related to quadratic unbiased estimation of variance components. It is argued that these methods of estimation of variance components essentially generalize LSE though they are not formally equivalent.